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"""SQLAlchemy models for the energy pricing and DSMR metering subsystem.
Six tables:
- meter: physical electricity meter lifecycle epoch.
- dsmr_reading: raw DSMR telegram blobs (10-second down-sampled).
- energy_contract: contract head (manual or tibber, one active at a time).
- energy_contract_version: versioned pricing values; append-only for auditability.
- tibber_price: cached Tibber 15-minute spot prices (immutable).
- energy_cost_period: computed 15-minute billing periods (immutable snapshot).
"""
from __future__ import annotations
import uuid as _uuid
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from datetime import datetime, timezone
from decimal import Decimal
from typing import Any
from sqlalchemy import (
Boolean,
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CheckConstraint,
DateTime,
Float,
ForeignKey,
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Index,
Integer,
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Numeric,
String,
UniqueConstraint,
event,
text,
)
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from sqlalchemy.orm import Mapped, mapped_column, relationship, synonym, validates
from sqlalchemy.types import JSON, TypeDecorator
from app.db import Base
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from app.models.meter_source import MeterSourceBinding
def _uuid4_str() -> str:
return str(_uuid.uuid4())
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def _decimal_json(value: Any) -> Any:
"""Make auditable JSON portable without admitting binary numeric values."""
if isinstance(value, Decimal):
return format(value, "f")
if isinstance(value, float) or (isinstance(value, int) and not isinstance(value, bool)):
raise ValueError("JSON amounts and quantities must be decimal strings, not numeric JSON values")
if isinstance(value, dict):
return {key: _decimal_json(child) for key, child in value.items()}
if isinstance(value, list):
return [_decimal_json(child) for child in value]
return value
def _validate_fixed_decimal(value: Decimal, precision: int, scale: int, field: str) -> Decimal:
if not isinstance(value, Decimal):
raise ValueError(f"{field} must be a Decimal, not a binary float or other numeric type")
if not value.is_finite():
raise ValueError(f"{field} must be finite")
if -value.as_tuple().exponent > scale:
raise ValueError(f"{field} exceeds scale {scale}")
integer_digits = 0 if value.is_zero() else max(value.copy_abs().adjusted() + 1, 0)
if integer_digits > precision - scale:
raise ValueError(f"{field} exceeds precision {precision},{scale}")
return value
class ExactDecimal(TypeDecorator[Decimal]):
"""Fixed-point Decimal which uses SQLite TEXT, never a binary float."""
impl = Numeric
cache_ok = True
def __init__(self, precision: int, scale: int) -> None:
self.precision = precision
self.scale = scale
super().__init__(precision=precision, scale=scale)
def load_dialect_impl(self, dialect):
if dialect.name == "sqlite":
return dialect.type_descriptor(String(self.precision + 2))
return dialect.type_descriptor(Numeric(self.precision, self.scale, asdecimal=True))
def process_bind_param(self, value: Decimal | None, dialect) -> Decimal | str | None:
if value is None:
return None
value = _validate_fixed_decimal(value, self.precision, self.scale, "decimal value")
if dialect.name == "sqlite":
return format(value, f".{self.scale}f")
return value
def process_result_value(self, value: Decimal | str | None, _dialect) -> Decimal | None:
return None if value is None else Decimal(value)
class DecimalJSON(TypeDecorator[dict]):
"""JSON which serializes Decimal values as strings on every write path."""
impl = JSON
cache_ok = True
def process_bind_param(self, value: Any, _dialect) -> Any:
return None if value is None else _decimal_json(value)
class UTCDateTime(TypeDecorator[datetime]):
"""UTC timestamps that preserve instant identity on SQLite and other dialects."""
impl = DateTime(timezone=True)
cache_ok = True
def __init__(self, field: str) -> None:
self.field = field
super().__init__()
def process_bind_param(self, value: datetime | None, _dialect) -> datetime | None:
return None if value is None else _normalise_utc_period(value, self.field)
def process_result_value(self, value: datetime | None, _dialect) -> datetime | None:
if value is None:
return None
if value.tzinfo is None or value.utcoffset() is None:
return value.replace(tzinfo=timezone.utc)
return value.astimezone(timezone.utc)
def _require_aware_period(start: datetime, end: datetime) -> None:
if start.tzinfo is None or start.utcoffset() is None:
raise ValueError("period_start must be timezone-aware")
if end.tzinfo is None or end.utcoffset() is None:
raise ValueError("period_end must be timezone-aware")
if end <= start:
raise ValueError("period_end must be after period_start")
def _normalise_utc_period(value: datetime, field: str) -> datetime:
if value.tzinfo is None or value.utcoffset() is None:
raise ValueError(f"{field} must be timezone-aware")
return value.astimezone(timezone.utc)
class Meter(Base):
"""One physical electricity meter's installation epoch.
A ``meter`` record represents the period ``[started_at, ended_at)`` during
which a particular physical meter was installed and active. Replacing a meter
(swap, home move, etc.) is modelled by closing the current record
(``ended_at = swap_timestamp``) and opening a new one
(``started_at = swap_timestamp``).
**Invariant**: for each ``commodity`` there is at most one active meter
(``ended_at IS NULL``) at any point in time. The service layer enforces
this — no DB-level constraint is added to keep the migration simple and to
allow the application to return a meaningful error message.
``commodity`` defaults to ``"electricity"``; the field is a free-form string
(no CHECK constraint) so future commodities (``gas``, ``heating``) can be
added without a schema change.
``reason`` captures why this epoch started — one of ``initial``,
``meter_swap``, ``home_move``, or ``other`` — stored as a plain string so
the application layer controls the allowed set.
"""
__tablename__ = "meter"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
# Stable internal identity — used as HA Discovery unique_id anchor.
uuid: Mapped[str] = mapped_column(String(36), unique=True, nullable=False, default=_uuid4_str)
# Human-readable label for this physical meter (e.g. address, serial, tariff zone).
label: Mapped[str] = mapped_column(String(255), nullable=False)
# Energy commodity this meter measures. Defaults to "electricity".
commodity: Mapped[str] = mapped_column(String(32), nullable=False, default="electricity")
# UTC timestamp when this meter epoch starts (inclusive). May be in the past
# (retroactive declaration); effective billing start = max(started_at, data start).
started_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
# UTC timestamp when this meter epoch ends (exclusive). NULL = currently active.
ended_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
# Why this epoch was created. Application-layer validation enforces the
# allowed set; no CHECK constraint to keep migrations simple.
reason: Mapped[str] = mapped_column(String(64), nullable=False)
# Free-form note (e.g. location, physical meter id, reason details).
note: Mapped[str | None] = mapped_column(String(1024), nullable=True)
# UTC timestamp of when this row was created.
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
# Relationship to cost periods attributed to this meter epoch (not loaded eagerly).
cost_periods: Mapped[list["EnergyCostPeriod"]] = relationship(
back_populates="meter", cascade="save-update, merge"
)
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source_bindings: Mapped[list["MeterSourceBinding"]] = relationship(
back_populates="meter", cascade="save-update, merge"
)
class DsmrReading(Base):
"""One down-sampled DSMR telegram stored as a full JSON blob.
Identity & idempotency are **independent of the DSMR Reader's telegram id**
(that field overflows and must be manually reset to zero — a known DSMR
quirk — so relying on it for uniqueness risks silently dropping new data).
The table's own autoincrement ``id`` PK is the stable internal identity, and
``(meter_source_id, recorded_at)`` is the UNIQUE de-duplication key: each
configured P1 source emits at most one telegram per timestamp, while
different sources may legitimately emit at the same instant.
``recorded_at`` is a real column (not inside the payload) so time-range
queries are efficient. The entire telegram frame is stored verbatim in
``payload``; no field allow-list is applied so future commodities (gas,
heating, three-phase) are accommodated without a schema change.
"""
__tablename__ = "dsmr_reading"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
# UTC timestamp of the sample. Idempotency is per configured source, so
# distinct P1 sources may legitimately emit at the same instant.
recorded_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
# Telegram's own id (DSMR Reader assigns it). Stored only as a reference /
# debugging aid — NOT used for uniqueness or idempotency (it overflows and
# gets reset to zero). Nullable because some DSMR sources may not emit one.
telegram_id: Mapped[int | None] = mapped_column(Integer, nullable=True)
# Compatibility for the pre-M8 ingest implementation. This is an ORM
# alias only; the physical database column is ``telegram_id``.
source_id = synonym("telegram_id")
# The configured source is the durable identity of the cumulative reading
# stream. It is non-null after the revision-16 historical adoption.
meter_source_id: Mapped[int] = mapped_column(
ForeignKey("meter_source.id", ondelete="RESTRICT"), nullable=False, index=True
)
# Full telegram frame as a JSON object; values are typically JSON strings
# (e.g. "20915.154") — callers must cast to Decimal before arithmetic.
payload: Mapped[dict] = mapped_column(JSON, nullable=False)
__table_args__ = (
UniqueConstraint(
"meter_source_id", "recorded_at", name="uq_dsmr_reading_source_recorded_at"
),
)
@event.listens_for(DsmrReading, "before_insert")
def _supply_legacy_dsmr_source(_mapper, connection, target: DsmrReading) -> None:
"""Keep the pre-T04 single-source writer working during the schema handoff."""
if target.meter_source_id is None:
target.meter_source_id = connection.execute(
text("SELECT id FROM meter_source WHERE kind = 'dsmr_mqtt' ORDER BY id LIMIT 1")
).scalar_one()
class EnergyContract(Base):
"""Contract head: a named energy contract with a chosen pricing strategy.
``kind`` determines which price strategy is used (``manual`` for fixed
dual-tariff rates entered by the user, ``tibber`` for dynamic API prices).
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A contract belongs to an energy ``scope`` (currently electricity; thermal
profiles are reserved for the next milestone). Only one contract may be
``active`` per scope; the service layer enforces mutual exclusion. Specific
pricing values live in ``EnergyContractVersion``
so that price changes can be tracked without modifying historical records.
"""
__tablename__ = "energy_contract"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
# Human-readable label; freely editable by the user.
name: Mapped[str] = mapped_column(String(255), nullable=False)
# Strategy selector: "manual" or "tibber". Application-layer validation
# enforces the allowed set; no DB CHECK constraint is added to keep the
# migration simple and the strategy registry extensible.
kind: Mapped[str] = mapped_column(String(32), nullable=False)
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# Billing domain. The service registry derives this from ``kind`` so API
# callers cannot move a pricing strategy into an incompatible domain.
scope: Mapped[str] = mapped_column(
String(32), nullable=False, default="electricity", index=True
)
# Whether this is the currently active contract (at most one should be True).
active: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
# ISO 4217 currency code for all monetary values in this contract.
currency: Mapped[str] = mapped_column(String(8), nullable=False, default="EUR")
# Audit timestamps.
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
# Relationship to versions (back-reference; not loaded eagerly).
versions: Mapped[list["EnergyContractVersion"]] = relationship(
back_populates="contract", cascade="save-update, merge"
)
class EnergyContractVersion(Base):
"""One time-bounded version of an energy contract's pricing values.
Pricing changes are modelled as new versions (append-only); existing versions
are never modified so that historical ``EnergyCostPeriod`` records remain
fully auditable. ``effective_to`` is ``NULL`` for the currently open version.
"""
__tablename__ = "energy_contract_version"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
# FK to the parent contract. RESTRICT prevents deletion of a contract that
# still has versioned pricing rows attached to it.
contract_id: Mapped[int] = mapped_column(
ForeignKey("energy_contract.id", ondelete="RESTRICT"), nullable=False
)
# Start of this version's validity window (inclusive, UTC).
effective_from: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
# End of this version's validity window (exclusive, UTC). NULL means open-ended
# (i.e. this is the most recent / current version).
effective_to: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
# Pricing values as a JSON object conforming to the profile structure for
# ``contract.kind`` (validated by the application layer against the YAML profile).
values: Mapped[dict] = mapped_column(JSON, nullable=False)
# Creation timestamp.
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
# Relationship back to the parent contract.
contract: Mapped["EnergyContract"] = relationship(back_populates="versions")
# Relationship to cost periods that reference this version.
cost_periods: Mapped[list["EnergyCostPeriod"]] = relationship(
back_populates="contract_version", cascade="save-update, merge"
)
class TibberPrice(Base):
"""Cached Tibber 15-minute spot price point (immutable once fetched).
``starts_at`` is unique so that upserts are idempotent. Past prices are
never overwritten; the fetch job only adds rows for future time slots.
"""
__tablename__ = "tibber_price"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
# UTC start of the 15-minute slot; unique so upsert is idempotent.
starts_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, unique=True
)
# Resolution label as returned by the Tibber API (e.g. "QUARTER_HOURLY").
resolution: Mapped[str] = mapped_column(String(32), nullable=False)
# Price components in the contract currency (all include VAT, user-facing).
energy: Mapped[float] = mapped_column(Float, nullable=False)
tax: Mapped[float] = mapped_column(Float, nullable=False)
total: Mapped[float] = mapped_column(Float, nullable=False)
# Tibber price level (e.g. "NORMAL", "CHEAP", "EXPENSIVE"); may be absent.
level: Mapped[str | None] = mapped_column(String(32), nullable=True)
# ISO 4217 currency code as returned by the API.
currency: Mapped[str] = mapped_column(String(8), nullable=False)
# UTC timestamp of when this row was fetched/inserted.
fetched_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
class EnergyCostPeriod(Base):
"""Computed billing record for one 15-minute metering period (immutable snapshot).
Each row captures the per-register kWh deltas, the resulting import cost and
export revenue, and a full snapshot of the pricing values used so that the
calculation is fully auditable and reproducible without re-querying the
contract version. Rows are written once and never modified; explicit
recomputation via the API is the only way to overwrite a period.
"""
__tablename__ = "energy_cost_period"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
# UTC start of the 15-minute period; unique so upsert is idempotent.
period_start: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, unique=True
)
# Per-register kWh deltas for the period (end minus start of cumulative registers).
# _1 = dal/low-tariff, _2 = normal/high-tariff (NL convention).
d1_kwh: Mapped[float] = mapped_column(Float, nullable=False) # delivered low
d2_kwh: Mapped[float] = mapped_column(Float, nullable=False) # delivered high
r1_kwh: Mapped[float] = mapped_column(Float, nullable=False) # returned low
r2_kwh: Mapped[float] = mapped_column(Float, nullable=False) # returned high
# Computed monetary amounts for the period (in ``currency``).
import_cost: Mapped[float] = mapped_column(Float, nullable=False)
export_revenue: Mapped[float] = mapped_column(Float, nullable=False)
net_cost: Mapped[float] = mapped_column(Float, nullable=False)
# ISO 4217 currency code matching the contract.
currency: Mapped[str] = mapped_column(String(8), nullable=False)
# Full snapshot of the pricing inputs used during computation. This makes
# each row self-contained and auditable even if the contract is later changed.
pricing: Mapped[dict] = mapped_column(JSON, nullable=False)
# FK to the exact contract version whose values were used. RESTRICT prevents
# deletion of a version that has cost records attached. Nullable to support
# periods computed in ``degraded`` mode (missing price data).
contract_version_id: Mapped[int | None] = mapped_column(
ForeignKey("energy_contract_version.id", ondelete="RESTRICT"), nullable=True
)
# FK to the meter epoch this period belongs to. RESTRICT prevents deletion of
# a meter that still has attributed cost periods. Nullable for backwards
# compatibility (pre-M7 rows) and degraded periods where the meter was not
# determinable.
meter_id: Mapped[int | None] = mapped_column(
ForeignKey("meter.id", ondelete="RESTRICT"), nullable=True
)
# Nullable for historical and degraded rows. Every new normal period
# points at the one binding that supplied both cumulative endpoints.
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source_binding_id: Mapped[int | None] = mapped_column(
ForeignKey("meter_source_binding.id", ondelete="RESTRICT"), nullable=True
)
# True when the period was computed with incomplete data (missing readings or
# missing price); serves as a flag for later recomputation.
degraded: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
# UTC timestamp of when this row was computed/inserted.
computed_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
# Relationship back to the contract version.
contract_version: Mapped["EnergyContractVersion | None"] = relationship(
back_populates="cost_periods"
)
# Relationship back to the meter epoch.
meter: Mapped["Meter | None"] = relationship(back_populates="cost_periods")
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source_binding: Mapped["MeterSourceBinding | None"] = relationship(
back_populates="cost_periods"
)
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class MeterCostPeriod(Base):
"""Auditable commodity-scoped ledger row for one half-open metering period.
A degraded row intentionally permits missing audit links; services must
still require them before writing a normal row.
"""
__tablename__ = "meter_cost_period"
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
commodity: Mapped[str] = mapped_column(String(32), nullable=False)
period_start: Mapped[datetime] = mapped_column(UTCDateTime("period_start"), nullable=False)
period_end: Mapped[datetime] = mapped_column(UTCDateTime("period_end"), nullable=False)
meter_id: Mapped[int | None] = mapped_column(
ForeignKey("meter.id", ondelete="RESTRICT"), nullable=True
)
source_binding_id: Mapped[int | None] = mapped_column(
ForeignKey("meter_source_binding.id", ondelete="RESTRICT"), nullable=True
)
contract_version_id: Mapped[int | None] = mapped_column(
ForeignKey("energy_contract_version.id", ondelete="RESTRICT"), nullable=True
)
# SQLite reliably round-trips at most fifteen significant decimal digits.
# WarmteLink itself reports 0.001 units, so nine cost fractional digits
# retain a six-place tariff times that source precision without float loss.
quantity: Mapped[Decimal] = mapped_column(ExactDecimal(15, 6), nullable=False)
cost: Mapped[Decimal] = mapped_column(ExactDecimal(15, 9), nullable=False)
currency: Mapped[str] = mapped_column(String(8), nullable=False)
cost_breakdown: Mapped[dict] = mapped_column(DecimalJSON(), nullable=False, default=dict)
pricing_snapshot: Mapped[dict] = mapped_column(DecimalJSON(), nullable=False, default=dict)
quality: Mapped[str] = mapped_column(String(32), nullable=False, default="valid")
degraded: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
degraded_reason: Mapped[str | None] = mapped_column(String(255), nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
meter: Mapped["Meter | None"] = relationship()
source_binding: Mapped["MeterSourceBinding | None"] = relationship()
contract_version: Mapped["EnergyContractVersion | None"] = relationship()
__table_args__ = (
CheckConstraint(
"degraded OR (meter_id IS NOT NULL AND source_binding_id IS NOT NULL "
"AND contract_version_id IS NOT NULL)",
name="ck_meter_cost_period_normal_audit_links",
),
CheckConstraint("period_end > period_start", name="ck_meter_cost_period_positive_interval"),
CheckConstraint(
"NOT degraded OR (degraded_reason IS NOT NULL AND length(trim(degraded_reason)) > 0)",
name="ck_meter_cost_period_degraded_reason",
),
UniqueConstraint("commodity", "period_start", name="uq_meter_cost_period_commodity_start"),
Index("ix_meter_cost_period_commodity_start", "commodity", "period_start"),
Index("ix_meter_cost_period_source_binding_id", "source_binding_id"),
)
@validates("cost_breakdown", "pricing_snapshot")
def _validate_decimal_json(self, _key: str, value: dict) -> dict:
return _decimal_json(value)
@validates("quantity", "cost")
def _validate_fixed_decimal(self, key: str, value: Decimal) -> Decimal:
precision, scale = (15, 6) if key == "quantity" else (15, 9)
return _validate_fixed_decimal(value, precision, scale, key)
@validates("period_start", "period_end")
def _normalise_period(self, key: str, value: datetime) -> datetime:
return _normalise_utc_period(value, key)
@event.listens_for(MeterCostPeriod, "before_insert")
@event.listens_for(MeterCostPeriod, "before_update")
def _validate_meter_cost_period(_mapper, _connection, target: MeterCostPeriod) -> None:
_require_aware_period(target.period_start, target.period_end)
if not target.degraded and (
target.meter_id is None
or target.source_binding_id is None
or target.contract_version_id is None
):
raise ValueError("normal meter cost periods require meter, binding, and contract version")
if target.degraded and not target.degraded_reason:
raise ValueError("degraded meter cost periods require a degraded_reason")
# Index on recorded_at for efficient time-range queries on DSMR readings.
# (The ORM-level index=True on recorded_at already creates ix_dsmr_reading_recorded_at;
# no composite index is needed for single-meter deployments.)
# Index on period_start is covered by the unique constraint (SQLite creates an
# implicit index for UNIQUE columns), so no additional index is required.
# Index on starts_at for TibberPrice is covered by the unique constraint similarly.